Weight generation in stationary interference and noise environments

ABSTRACT

An apparatus for performance improvement of a digital wireless receiver comprises a processing circuit for processing a plurality of received signals and providing a processed signal, wherein a plurality of weights is applied to the plurality of received signals producing a plurality of weighted received signals. The plurality of weighted received signals are combined to provide the processed signal. A weight generation circuit generates the plurality of weights wherein weights are based on a ratio of a desired signal, a noise signal and an interference signal.

CROSS REFERENCES TO RELATED APPLICATIONS

This application is related to copending U.S. patent application Ser.No. 08/847,956 entitled "Adaptive Antenna Array Processing ArrangementUsing A Combined Coherent And Constant-Modulus Reference Signal" filedon Apr. 22, 1997, copending U.S. patent application Ser. No. 08/865,566,entitled "DC Offset Compensation Using Antenna Arrays" filed on May 29,1997,copending U.S. patent application Ser. No. 08/756,293, entitled"Artificial Fading for Frequency Offset Mitigation" filed on Nov. 25,1996, which is a continuation of U.S. patent application Ser. No.08/716,659, entitled "Joint Timing, Frequency And Weight Acquisition Foran Adaptive Array" filed on Sep. 6, 1996, and a continuation ofcopending U.S. patent application Ser. No. 08/606,777, entitled"Introducing Processing Delay As A Multiple Of The Time Slot Duration"filed on Feb. 27, 1996 and a continuation of copending U.S. patentapplication Ser. No. 08/695,492, entitled "Output Signal ModificationFor Soft Decision Decoding" filed on Aug. 12, 1996.

FIELD OF THE INVENTION

The present invention relates to the field of wireless communication andmore particularly to digital wireless communications systems.

BACKGROUND OF THE INVENTION

In wireless communication systems, the use of antenna arrays at the basestation has been shown to increase both range, through increased gain,and capacity, through interference suppression. With adaptive antennaarrays, the signals received by multiple antenna elements are weightedand combined to improve system performance, e.g., by maximizing thedesired receive signal power and/or suppressing interference. Theperformance of an adaptive antenna array increases dramatically with thenumber of antennas. Referring to an article entitled, "The Impact ofAntenna Diversity on the Capacity of Wireless Communication Systems," byJ. H. Winters, R. D. Gitlin and J. Salz, in IEEE Trans. onCommunications, April 1994, it is shown that using an M element antennaarray with optimum combining of the received signals can eliminate N≦M-1interferers and achieve an M-N fold diversity gain against multipathfading, resulting in increased range.

Most base stations today, however, utilize only two receive antennaswith suboptimum processing, e.g., selection diversity where the antennahaving the larger signal power is selected for reception and processing.It is desirable to be able to modify existing base stations toaccommodate larger arrays of antennas and/or improved received signalcombining techniques. However, modifying existing equipment isdifficult, time consuming, and costly, in particular since equipmentcurrently in the field is from a variety of vendors.

One alternative is to use a so called applique, which is an outboardsignal processing box, interposed between the current base antennas andthe input to the base station, and which adaptively weights and combinesthe received signals fed to the base station, optionally uses additionalantennas. A key to the viability of using the applique approach is thatit should require little, if any, modification of the base stationequipment. This implies that the processing performed by the appliquemust be transparent to the existing equipment. Ideally, the signalemerging from the applique should appear to the existing base station asa high-quality received signal from a single antenna.

The signal processing functions performed by an adaptive array aretypically designed to maximize the signal to interference-plus-noiseratio. One well known method for accomplishing this is by adjusting theadaptive array weights so as to minimize the mean squared error of theoutput signal with respect to a reference signal. Two common techniquesfor reference signal generation that are well known in the art arecoherent reference and constant-modulus reference, the latter also beingknown in the art as the constant-module algorithm (CMA).

In light of the above considerations there is therefore a need foradaptive array weight generation that increases gain and improvesinterference suppression.

SUMMARY OF THE INVENTION

In accordance with the present invention, there is provided an apparatusfor performance improvement of a digital wireless receiver. Theapparatus comprises a processing circuit for processing a plurality ofreceived signals and providing a processed signal, wherein a pluralityof weights is applied to the plurality of received signals producing aplurality of weighted received signals. The plurality of weightedreceived signals are combined to provide the processed signal. A weightgeneration circuit generates the plurality of weights in which thevalues of the weights are based on a ratio of a desired signal, a noisesignal and an interference signal.

BRIEF DESCRIPTION OF THE DRAWINGS

A more complete understanding of the present invention may be obtainedfrom consideration of the following description in conjunction with thedrawings in which:

FIG. 1 is a block diagram of an adaptive array using multiple antennas;

FIG. 2 is a graphical representation of BER versus S/N for 2 and 4antennas;

FIG. 3A and 3B show a TDMA frame and time slot architecture of an uplinkdigital traffic channel used in IS-136.

FIG. 4 is a graphical representation of BER versus K with a 184 Hzfading rate;

FIG. 5 is a graphical representation of BER versus S/N of DMI with noiseonly; and,

FIG. 6 is a graphical representation of BER versus S/N when interferenceis not present.

DETAILED DESCRIPTION OF VARIOUS ILLUSTRATIVE EMBODIMENTS

Although the present invention is particularly well suited for use inTime Division Multiple Access (TDMA) mobile radio systems, such as NorthAmerican Digital Mobile Radio Standard IS-136, and shall be describedwith respect to this application, the methods and apparatus disclosedhere can be applied to other digital wireless communication systems.Other systems include but are not limited to the North American MobileRadio Standard IS-54, the Groupe Speciale Mobile (GSM) based system,also known as Global System for Mobile Communications, which is astandard digital cellular phone service used in Europe and Japan, andthe Digital European Cordless Telecommunications (DECT) based system,which is a pan-European digital cordless telephony interfacespecification. Although the present invention is suited for use with anapplique and shall be described with respect to this application, themethods and apparatus disclosed here are equally well suited to anintegrated application of adaptive arrays in a base station.

Referring to FIG. 1 there is shown a block diagram of a type of signalprocessing used in a base station applique. In one embodiment, thesignal processor provides the necessary circuitry for weight generationbased on a noise-plus-interference. A signal u(t) transmitted by amobile station 10 through a mobile antenna 12 is received by a basestation 16 from M antennas 18, with received signals x₁ (k) to x_(M) (k)respectively. The received signals are weighted using multipliers 20having weights w₁ (k) to w_(M) (k) respectively, to generatecorresponding weighted signals w₁ (k)x₁ (k) to w_(M) (k)x_(M) (k). Theweighted signals w₁ (k)x₁ (k) to w_(M) (k)x_(M) (k) are then combinedusing summer 24 to generate an output signal y(k) which is then providedto base station equipment 16. Weights w₁ (k) to w_(M) (k) are generatedby weight generation circuitry 22 based upon computations performed uponreceived signals x₁ (k) to x_(M) (k) and output signal y(k). At theapplique processor circuitry 14, received signals x₁ (k) to x_(M) (k)are weighted and combined to improve signal quality at the output.

With the correct symbol timing and carrier frequency, the weights can begenerated to combine the signals received from multiple antennas toincrease gain and suppress interference, permitting operation even withnoise and/or interference power that is greater than the signal power.

Weight Generation--Ideal Tracking Performance

The complex baseband signal received by the ith element in the kthsymbol interval x_(i) (k) is multiplied by a controllable complex weightw_(i) (k) producing a weighted signal. The weighted signals are thensummed to form the array output y(k). Thus, the output signal is givenby

    y(k)=w.sup.T (k)×(k),                                (1)

where the weight vector w is given by

    w= w.sub.1 w.sub.2 . . . w.sub.M !.sup.T,                  (2)

the superscript T denotes transpose, and the received signal vector x isgiven by

    x= x.sub.1 x.sub.2 . . . x.sub.M !.sup.T.                  (3)

The received signal consists of the desired signal, thermal noise, andinterference and, therefore can be expressed as ##EQU1## where x_(d) isthe received desired signal, x_(n) is the received noise signal andx_(j) is the jth interfering signal vector, and L is the number ofinterferers. Furthermore, let s_(d) (k) and s_(j) (k) be the desired andjth interfering signals, with

    E |s.sub.d (k)|.sup.2 !=1,               (5)

and

    E |s.sub.j (k)|.sup.2 !=1 for 1<j<L.     (6)

Then x can be expressed as ##EQU2## where u_(d) and u_(j) are thedesired and jth interfering signal propagation vectors, respectively.

The received signal correlation matrix is given by ##EQU3## where thesuperscript * denotes complex conjugate and the expectation is takenwith respect to the signals s_(d) (k) and s_(j) (k), and the receivednoise signal x_(n). Assuming the desired, noise, and interfering signalsare uncorrelated, the expectation evaluates to yield ##EQU4## where σ²is the noise power and I is the identity matrix. Note that R_(xx) varieswith the fading and that we have assumed that the fading rate is muchless than the symbol rate. We define the received desiredsignal-to-noise ratio S/N as ##EQU5## the interference to noise ratio(INR) as (for the jth, j=1, L, interferer) ##EQU6## and thesignal-to-interference-plus-noise ratio (SINR) as ##EQU7## where theexpected value now is with respect to the propagation vectors.

For the digital mobile radio system IS-136 without interference, theweights that minimize the bit error rate (BER) also minimize the meansquared error (MSE) in the output signal, where the error is thedifference between the output signal y(k) and a reference signal d(k),which ideally is the transmitted data s_(d) (k). With interference, theweights that minimize the MSE also reduce the output signal BER, but donot necessarily minimize the BER. However, the minimum MSE (MMSE)weights are typically utilized in this case as well since they are moremathematically tractable and yield results that are typically close tothe minimum BER weights. The MMSE weights, which also maximize theoutput SINR, are given by

    w(k)=R.sub.xx.sup.-1 (k)r.sub.xd (k)                       (13)

where

    r.sub.xd (k)=E x(k)*d(k)!=u.sub.d                          (14)

and the superscript -1 denotes the inverse of the matrix. In Equation(3), R_(xx) is assumed to be nonsingular so that R_(xx) ⁻¹ exists. Ifnot, pseudoinverse techniques can be used to solve for w.

First consider the performance of MMSE combining with a perfectknowledge of R_(xx) and r_(xxd). Assume independent Rayleigh fading ateach antenna and no delay spread, and determine the BER averaged overthe fading with differential detection of the π/4-shifted differentialquadrature phase shift keyed signal (DQPSK) signal of IS-136. Withinterference, the BER was determined by Monte Carlo simulation.

FIG. 2 shows the BER versus S/N for 2 and 4 antennas. For each datapoint the BER is averaged over 29,000 symbols. Results are shown havingnoise only, both with and without desired signal fading, and with aninterferer with the same power (averaged over the fading) as the desiredsignal with fading of both the desired and interfering signals. Theseresults show that with fading and no interference, the required S/N fora 10² BER is reduced by 6 dB with 4 versus 2 antennas. This correspondsto about 40% greater range in environments with a 4th law power lossexponent. Also, this required S/N with 4 antennas and fading is 2 dBlower than that required with 2 antennas without fading. Furthermore,even with an equal power interferer, the required S/N is 4 dB lower with4 antennas than with 2 antennas and no interference. Thus, a fourantenna base station can theoretically achieve both greater range andhigher capacity on the uplink than a current two-antenna base station.

Weight Tracking with Direct Matrix Inversion

Consider the implementation of MMSE combining using direct matrixinversion (DMI) (also known as sample covariance matrix inversion).Using a rectangular averaging window, the weights are given by

    w(k+1)=R.sub.xx.sup.-1 (k)r.sub.xd (k),                    (15)

where ##EQU8## and K is the window length.

Referring to FIG. 3A there is shown the TDMA frame 70 and time slots 72.In each frame, a user is given two time slots (full rate), e.g., timeslots 3 and 6. Referring to FIG. 3B there is shown in detail a time slotstructure 72 of IS-136 uplink (mobile station to base station) digitaltraffic channel. This is a TDMA frame structure, wherein datatransmitted from each mobile station (cellular phone) user istransmitted periodically in time slots 72 or "bursts". There are 6 timeslots 72 defined per frame 70. The duration of frame 70 is 40 ms, andeach time slot 72 is one-sixth of the frame duration, approximately 6.7ms. Each time slot 72 comprises 162 symbols, including synchronization(SYNC) sequence 74, SYNC 74 comprising symbols 15 through 28. Thissynchronization sequence is fixed and known a priori at the receiver.For uplink transmission, each time slot consists of 3 guard symbols 76,3 ramp symbols 78, 130 data symbols 80, a 14 symbol synchronization(SYNC) sequence 74, a 6 symbol SACCH 82 sequence, and a 6 symbol CDVCC84 sequence. The synchronization sequence 74 is known at the basestation and is used to acquire the initial weights. Thus,synchronization sequence 74 is used as the reference signal foracquisition, and subsequently the coherently detected data is used asthe reference signal, i.e.,

    d(k)=quan(w.sup.T (k)×(k))                           (18)

where quan (·) denotes π/4 QPSK coherent detection. Note coherentdetection for the reference signal has been considered even thoughdifferential detection was assumed for the base station. This is becausethe weight generation algorithms that are of interest require a coherentreference signal, and coherent detection requires about a 1 dB lower S/Nfor the same BER, and thus is more reliable.

The performance with the DMI weights given by Equation (15) will beworse than the performance with the ideal tracking weights given byEquation (13) because of three factors. First, the transmission channelcan vary over the window of length K. For example a 1.9 GHz carrierfrequency with vehicle speeds up to 60 mph, corresponds to fading ratesas high as 184 Hz. At these rates, the phase of the transmissionchannels can change a few degrees each symbol. The weights calculatedover the K symbol window are used to generate the output signal andreference signal sample just after the window. Thus, the degradation dueto channel variation increases with K.

A second degradation is due to noise in the weight calculation. The S/Ndegradation due to noise depends on the ratio of K to the number ofweights, M. For an M=4 and K=8 the degradation is about 3 dB, and thedegradation decreases with increasing K.

A third degradation is due to error propagation. With acoherently-sliced data-derived reference signal, detection errorsincrease the error in the weights. Since this increases the BER, errorpropagation can occur, resulting in a complete loss of tracking and alarge error burst that can last until the end of the time slot. Thedegradation due to detection errors decreases with increasing K.

FIG. 4 shows the BER versus K for the above three degradations with a184 Hz fading rate. Two cases are shown: 1) S/N=4.5 dB with noise only,and 2) S/N=6.5 dB with an equal power interferer (S/I=0 dB). Theseresults are for coherent detection of the array output signal, butsimilar conclusions were obtained with differential detection. TheseS/N's were chosen because they result in a 10⁻² BER with ideal weights.FIG. 4 shows the performance with channel variation only (known R_(xx)and r_(xd), but averaged over a rectangular window of length K), withchannel variation and noise (Equation (15) with an ideal referencesignal), and with all three impairments. With channel variation only,the degradation is shown to increase montonically with K When the effectof noise in the estimation is also included, the BER is seen to bedominated by the effect of noise for small K. Error propagation is seento dominate the other two effects, especially with small K, but the BERdecreases with K until the effect of channel variation becomessignificant. Error propagation is seen to dominate the other twoeffects, especially with small K. As a result, the BER decreases with Kuntil K is about 14, but remains about the same for K>14. Thus, a windowsize of 14 yields close to the best performance for these cases.However, note that the cases studied have an order of magnitude increasein BER due the degradations even with K=14.

FIG. 5 shows the BER versus S/N of DMI with noise only. Results areshown for the ideal weights given by Equation (13) with 2 and 4 antennasat 0 and 184 Hz fading, with DMI with 4 antennas at 0 and 184 Hz fadingand K=14. Note that even with the ideal weights the BER increases at 184Hz because of the channel variation over each symbol. With DMI, therequired S/N for a 10⁻² BER is increased by 1.2 and 2.7 dB at 0 and 184Hz, respectively. Thus, at 184 Hz, the implementation loss in gain isnearly half (in dB) the theoretical gain achieved with 4 versus 2antennas.

Methods to Improve Weight Tracking

The estimation error in calculating M weights with K samples depends onthe ratio K/M. Specifically, this is related to the fact M(M+1)/2complex terms of R_(xx) are estimated (since R_(xx) is Hermitian) and Mcomplex terms of r_(xd) are estimated. However, it can be noted from (9)it can be seen that R_(xx) actually consists of (L+1)M complex terms andone real scalar term (σ²), with the M terms that describe the desiredsignal channels the same terms as those in r_(xd). To remove those Mterms from R_(xx), consider the weights that maximize the SINR,

    w=R.sub.i+n.sup.-1 r.sub.xd,                               (19)

where ##EQU9## or

    R.sub.i+n=E (x-r.sub.xd *d)*(x-r.sub.xd *d).sup.T !.       (21)

These weights are the same as those given by Equation (13), except for ascale factor which doesn't matter for DQPSK. This algorithm can beimplemented as

    w(k)=R.sub.i+n.sup.31 1 (k)r.sub.xd (k)                    (22)

where ##EQU10## which yields similar performance to Equation (15) asverified by simulation results. Thus, if LM<M(M+1)/2, i.e., L<(M+1)/2,the weights can be more accurately calculated by determining the u_(j)'s, rather than all the terms of R_(xx),.

Specifically, for L=0, R_(i+n=)σ² I, and

    w(k)=r.sub.xd (k),                                         (24)

which are the weights for maximal ratio combining. Note that withmaximal ratio combining, the accuracy of the weights is independent ofM. Note also that the reason that DMI has poorer performance thanmaximal ratio combining when interference is not present because DMIconsiders the noisy cross correlation terms as being due to interferenceand tries to null this interference.

FIG. 6 shows the BER versus S/N with maximal ratio combining, Equation(24), when interference is not present. With the subspace method, thedegradation in required S/N for a given BER is less than 0.5 dB evenwith 184 Hz fading.

The use of Equation (24) requires that the noise-plus-interferencecorrelation matrix be given by

    R.sub.nn =σ.sup.2 I,                                 (25)

where σ² is the variance of the noise. However, the noise may not beequal on all antennas, e.g., when independent AGC's are used for eachantenna. In this case, the weight estimates of Equation (24) will not beoptimal. However, since in this case R_(nn) should be constant over manytime slots (i.e. vary at much slower than the fading rate), R_(nn) canbe estimated and then the weights can be given by

    w=R.sub.nn.sup.-1 r.sub.xd                                 (26)

Thus there is the same tracking accuracy as with Equation (24), sinceonly r_(xd) is calculated and R_(xx) is estimated over a long period oftime.

CONCLUSION

Embodiments of the present invention of an adaptive antenna array forIS-136 base stations provides range extension and cochannel interferencesuppression on the uplink. The adaptive weight generation algorithm isdirect matrix inversion using symbol-by-symbol sliding window weightcomputation. Simulation results showed the performance of this algorithmin 184 Hz fading (corresponding to 60 mph at 1.9 GHz) and found that atthese fading rates, there is significant tracking degradation. Thepresent invention provides enhancements to this algorithm to improveweight tracking performance in stationary interference and noiseenvironments. Real-time implementation and experimental test bed thatwas used to obtain real-time results using a fading channel emulator.For the most part, the real-time results tracked well with thesimulations, and discrepancies were well understood.

Experimental results using the enhanced algorithm for range extensionshowed more than 5 dB of the theoretical 6 dB higher gain at a 10⁻² BERin a Rayleigh fading environment than a current two element array usingpostdetection diversity combining. This corresponds to a 40% increase inrange in a typical mobile radio environment. When interferers arepresent, at slow speeds the four element array achieved more than 3 dBof the theoretical 4 dB higher gain with a cochannel interferer havingthe same average received signal power as the desired signal, ascompared to a two element array without interference. At 60 mph fadingrates, the results show that an interferer can reach nearly the level ofthe desired signal while maintaining a 10⁻² BER. This indicates thefeasibility of increased capacity through higher frequency reuse,perhaps even including the possibility of frequency reuse within a cell.

Numerous modifications and alternative embodiments of the invention willbe apparent to those skilled in the art in view of the foregoingdescription. Accordingly, this description is to be construed asillustrative only and is for the purpose of teaching those skilled inthe art the best mode of carrying out the invention. Details of thestructure may be varied substantially without departing from the spiritof the invention and the exclusive use of all modifications which comewithin the scope of the appended claim is reserved.

What is claimed is:
 1. An apparatus for performance improvement of adigital wireless receiver comprising:a processing circuit for processinga plurality of received signals and providing a processed signal,wherein a plurality of weights is applied to said plurality of receivedsignals producing a plurality of weighted received signals and saidplurality of weighted received signals are combined to provide saidprocessed signal; and a weight generation circuit for generating saidplurality of weights, wherein said plurality of weights are based on anoise-plus-interference correlation matrix estimated as constant over aplurality of time slots.
 2. The apparatus as recited in claim 1, whereinsaid plurality of received signals comprise TDMA mobile radio signals.3. The apparatus as recited in claim 2, wherein said TDMA mobile radiosignals comprise IS-136 based mobile radio signals.
 4. The apparatus asrecited in claim 2, wherein said TDMA mobile radio signals compriseIS-54 based mobile radio signals.
 5. The apparatus as recited in claim1, wherein said processing circuit comprises a digital signal processor.6. The apparatus as recited in claim 1, wherein said weight generationcircuit comprises a digital signal processor.
 7. A method forperformance improvement of a digital wireless receiver comprising thesteps of:processing a plurality of received signals; generating aplurality of weights based on a noise-plus-interference correlationmatrix estimated as constant over a plurality of time slots; applyingsaid plurality of weights to said plurality of received signalsproducing a plurality of weighted received signals; and combining saidplurality of weighted received signals producing a processed signal. 8.The method as recited in claim 7, wherein said plurality of receivedsignals comprise TDMA mobile radio signals.
 9. The method as recited inclaim 8, wherein said TDMA mobile radio signals comprise IS-136 basedmobile radio signals.
 10. The method as recited in claim 8, wherein saidTDMA mobile radio signals comprise IS-54 based mobile radio signals. 11.The method as recited in claim 7, wherein the step of generating aplurality of weights utilizes a digital signal processor.
 12. A signalprocessor for a wireless receiver comprising:a weight generation circuitfor generating a plurality of weights, wherein said plurality of weightsare based on a noise-plus-interference correlation matrix estimated asvarying slowly over a plurality of time slots; and, apparatus forcombining a plurality of received signals with respective ones of theweight values to provide a processed signal as a substitute for anoriginal received signal.
 13. The signal processor as recited in claim12 wherein said noise-plus-interference correlation matrix is estimatedas varying slower than a fading rate over a plurality of time slots. 14.The signal processor as recited in claim 12 wherein saidnoise-plus-interference correlation matrix is estimated as constantrelative to a fading rate over a plurality of time slots.